Regression Modeling Methods, Theory, and Computation with SAS

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs....

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Bibliographic Details
Main Author: Panik, Michael J. (Author)
Format: Book
Language:English
Published: Boca Raton CRC Press 2009
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Summary:Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs. The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression, L1 and q-quantile regression, regression in a spatial domain, ridge regression, semiparametric regression, nonlinear least squares, and time-series regression issues. For most of the regression methods, the author includes SAS procedure code, enabling readers to promptly perform their own regression runs.
Item Description:"A Chapman & Hall book."
Physical Description:xv, 814 pages illustrations 27 cm
Bibliography:Includes bibliographical references (pages 801-805) and index
ISBN:9781420091977
1420091972